Burrow is a desktop research canvas where notes, documents, and AI responses become editable objects on a board instead of disappearing into a chat transcript. Its project documentation describes workspaces stored as folders on your computer and supports local or hosted AI services. Voice input, however, requires a separately configured speech service: Burrow does not bundle a speech engine.
What Burrow is designed to do
Burrow targets open-ended research: work such as literature reviews, technical due diligence, and exploratory investigations. The project frames the problem as research material scattered between browser tabs, notes, PDFs, and memory. Its alternative is an infinite canvas where you can arrange material and return to it.
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The board supports notes, text, shapes, frames, tables, diagrams, documents, images, and freehand ink. The assistant can create and connect board objects, read imported documents, search the web and literature, and invoke image-generation tools. Because user and assistant edits use a shared command layer, the project says they participate in one undo history. These are capabilities described by the project, not results of independent product testing. Burrow’s repository
How workspaces are stored
Burrow represents a workspace as a folder on the user’s disk, with structured files for board state and related material. The repository’s example includes:
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workspace.jsonfor workspace metadata.board.jsonfor nodes, edges, ink, and the canvas viewport.transcript.jsonlas an append-only, text-only transcript.documents/andimages/directories for imported or used files.
The project says audio is not stored in the transcript. This describes the documented workspace format; it does not by itself establish that every provider interaction or application state is private or independently audited. Repository workspace documentation
What voice input requires
Voice is not ready to use offline immediately after installation. Burrow’s documented default path uses a Whisper-compatible server that the user runs separately. Examples in the project documentation include whisper.cpp, Speaches, LocalAI, and vLLM. The installer does not bundle a speech engine or model file. The project also names Groq, OpenAI, and Deepgram as hosted transcription options.
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In other words, choosing a local speech path means setting up and running a compatible service; choosing a hosted option means configuring an external provider. The documentation does not establish transcription quality, latency, or provider pricing, so those should not be assumed.
Always-on listening is opt-in
The repository describes an always-on mode that is off by default. When enabled, a local energy detector waits for speech, and transcription begins after the configured wake phrase. A visible indicator reports microphone state. Burrow also includes a microphone test intended to check capture, speech detection, and transcription. Actual behavior will depend on the configured service and the user’s platform. Voice setup documentation
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Model choices and data handling
The project describes support for Ollama and other OpenAI-compatible endpoints for local model operation, as well as user-supplied provider credentials. It says BYOK credentials are stored in the operating system keychain and characterizes configured provider calls as the data that leave the machine. Treat these as statements about the project’s documented design, not as an independent security audit or a guarantee about the handling practices of any external service.
For a setup intended to keep model processing local, users still need to configure a local endpoint; voice transcription also needs its own separately run local service if they want to avoid a hosted speech provider. Check the project’s current setup instructions for supported options and platform-specific details before configuring a workspace. Burrow repository and setup instructions
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What the project says is verified—and what is not
The repository calls Burrow usable and says its assistant loop and block types have been verified against live providers. It also reports document import and paper search working. The same documentation draws a boundary around less-established features:
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- Image generation is described as built, but not verified end to end with a live provider.
- The vision-based side of handwriting reading has not been tested with a model capable of seeing images.
An implemented interface or request format is not the same as a verified end-to-end feature. If image generation or handwriting recognition is central to your workflow, the repository’s stated status is a reason to confirm current behavior rather than rely on those capabilities. Feature status in the repository
Platforms and current setup details
Burrow’s listed application stack is Tauri v2, Rust, React 19, Vite, and TypeScript. The repository lists release options for Windows, macOS, and Linux, and notes that key storage and speech behavior can vary by operating system. Release binaries and installation steps may change, so use the repository’s current release and setup information rather than assuming a particular download or procedure applies to every platform. Current releases and platform instructions
Who may find Burrow useful
Burrow is most relevant if you want research materials arranged as persistent board objects, prefer to revisit and reorganize assistant output, and are comfortable configuring AI or speech services. Its local-folder workspace model and documented local-model options may suit people who want control over where their project files live, while provider calls and their data handling still depend on the services configured.
It may be a poor fit if you expect voice recognition to work immediately without setup, need independently validated privacy assurances, or depend on image generation or vision-based handwriting reading as proven capabilities. The project documentation does not establish a verified comparison with other research tools, so whether it is better than an existing workflow depends on your needs and configuration.
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